Individuals, or other entities, can be connected to each other in many different ways. For example, individuals may be genealogically connected to each other, such as by parent-child, sibling, or other types of relationships. The gathering of information regarding individuals and the relationships between individuals is generally referred to as genealogy. Typical gathered information might include dates and places of events such as birth, marriage, death, and other events that occur in the lives of individuals. Other types of information (e.g., medical, DNA, and disease tracking information) may also be gathered depending on the particular application of the data or the interests of the researcher.
Many tools exist for storing genealogical data and for representing the genealogical relationships between individuals. In particular, many genealogical tools exist that are able to represent relationships between families, ancestors, and descendants. One common genealogical tool is a pedigree chart, which visually represents relationships in the form of a tree. Another common genealogical tool is a group record (e.g., a family group record), which organizes individuals into a group.
These and other conventional genealogy tools have been implemented in software applications capable of operating on computing devices. The software applications typically have access to databases capable of storing vast amounts of genealogical information. The information contained in the databases, which is often organized by group records and/or event information, can be accessed and displayed in the form of pedigree charts or other similar tree-like representations of relationships. Such software applications leverage the significant computing power of modem computing devices to enhance the capabilities of traditional genealogical tools. In addition, conventional software applications provide for the sharing of genealogical data between different computing devices. For example, genealogical data communication (“GEDCOM”) format is a well-known data format used by many genealogical software programs for importing and exporting genealogical data.
While conventional genealogical tools have provided many benefits associated with representing relationships between individuals, several shortcomings are inherent in the conventional tools. These shortcomings are largely a result of reliance upon traditional theories underlying the use of pedigree charts (which are based on a family-tree paradigm), event information, and/or group records for organizing and representing genealogical data.
Pedigree and other tree-like charts tend to represent genealogical data in a cumbersome manner. This is largely due to the significant size of pedigree charts required to represent multiple generations. Due to the size of multi-generational pedigree charts, paper-based pedigree charts are generally fragmented onto different pieces of paper. The same fragmentation is also inherent in software applications, in which separate pedigree chart views are typically required to legibly depict the relationships between individuals of multiple generations. Such fragmented representations are less than intuitive and are often difficult to manipulate, piece together, and understand.
Genealogical tools using tree-like charts exhibit additional limitations. For example, conventional pedigree charts are not capable of intuitively differentiating the numerous possible types of relationships that may exist between individuals. A traditional pedigree chart typically includes nodes representative of individuals. The nodes are connected together by lines or other similar representations. Unfortunately, multiple connected nodes often share a common connection line having multiple branches. The common connection line is not useful for depicting different types of connections between the individuals. To further illustrate this limitation of conventional genealogical tools, FIG. 1 illustrates a tree-like representation of relationships between nodes, using a notation commonly used in anthropology. As shown in FIG. 1, a common line 10 branches to connect multiple nodes 12, 14, 16, 18, and 20 together. Such an arrangement is often used to depict the parent-child relationships between a parent and his or her children. Unfortunately, the use of a common line to connect multiple individuals is not useful for depicting any differences that may exist in each distinct parent-child relationship. For example, the tree-like chart of FIG. 1 is not useful for distinguishing an adoption relationship versus a natural-child relationship.
Pedigree charts are also limited in that they are able to represent only limited types of relationships. For example, a pedigree chart typically allows representation of only one spouse, one child, and one set of parents. This means that a pedigree chart cannot be used to represent a former spouse, multiple children, siblings, or both adoptive and biological parents. In other words, a single pedigree chart is not useful for representing many complex relationships that are common to society.
The rigid limitations of pedigree charts often require researchers to supplement pedigree charts with additional tools, such as group records or additional pedigree charts. Many conventional genealogical tools actually require that data be grouped into predefined group records. Unfortunately, the use of group records comes with limitations, including the fragmentation and duplication of data between various group records. For example, when an individual is connected to two separate group records, each of the group records typically contains duplicate information about the individual. For instance, a particular individual may be a child in a first family group record and a spouse in another family group record. Consequently, the information associated with the particular individual will either be fragmented or duplicated for each of the group records. Both options are undesirable for several reasons. The duplication of data wastes memory space and may lead to inconsistencies between data. Meanwhile, fragmented data may introduce complexity and costs to many typical genealogical application operations, such as searching for information. These problems are magnified by a lack of uniformity between different genealogical tools because one definition of a group record does not necessarily accommodate different definitions of group records.
Conventional genealogical database structures typically mirror pedigree-chart and/or group record representations of relationships. Accordingly, the conventional database structures tend to include the same inherent limitations discussed above. For example, conventional databases typically include records for individuals and/or groups. The records may include information associated with the individuals or with the relationships between the individuals. In particular, the records usually include information identifying other records to which there is a connection. For example, a group record is typically required and includes information identifying the individual records of an individual, the spouse, and the children. This type of database structure produces several undesirable limitations, including a lack of capability for associating information (e.g., link events) with a connection between individuals directly, since linkage is only implied by virtue of the method of grouping individual records into the same group record. Alternatively, conventional genealogical tools may associate such information with records of individuals. This often leads to the storing of duplicate information in more than one group or individual record, which is inefficient and wastes valuable memory space as discussed above. As an alternative to the duplication of data, genealogical information is often fragmented across multiple individual records, thereby introducing operational complexity into the database, which complexity undesirably limits search functionality by making it difficult for search operations to maneuver between records of individuals and groups.
Moreover, many conventional genealogical databases include event-based organizational structures, which further fragment genealogical data according to event-based information. For example, some large genealogical databases are fragmented by location information, such as a country of origin. This type of structuring introduces disconnectedness between individuals who might be otherwise connected to each other across geographic or national boundaries.
The fragmentation of genealogical information across conventional database boundaries (e.g., geographic boundaries) traditionally tended to introduce inconsistencies into the genealogical data. For example, personal names are invariably spelled in many different ways, requiring a variation-neutralizing algorithm and lookup table of names. In the past, databases contained many separate tables, each trained on a geographical area (e.g. countries), without cross-country correlation. A particular name variation would be handled differently in different tables. The lack of cross-correlation led to duplication of records, because name-variations were not neutralized identically for different countries, and records were not recognized as being duplications.
By relying solely, primarily, or heavily upon records of individuals and of groups of individuals for storing connection-based or other types of genealogical information, conventional database structures are not useful for robustly and flexibly representing and identifying myriad different types of relationships that may exist between individuals. Thus, conventional genealogical tools rely upon cumbersome, inefficient, unintuitive, and inflexible data organizational schema and visual representations. This is especially limiting for conventional genealogical tools that require group records for expressing relationships between individuals. Consequently, conventional genealogical tools are limited with respect to representing a wide variety of different types and characteristics of connectedness between individuals.